popeye

A population receptive field estimation tool

What is a population receptive field?

A population receptive field (pRF) is a quantitative model of the cumulative response of the population of cells contained within a single fMRI voxel [1]. The pRF model allows us to interpret and predict the responses of a voxel to different stimuli. Such models can be designed to describe various sensory [2] and cognitive processes [3]. The pRF model has been used to map the retinotopic organization of multiple subcortical nuclei [4].

Installation

Download the popeye source code from the GitHub repository. Links to the tarball and zip files are at the top of this page for your convenience. Using popeye requires that you have installed NumPy, SciPy, statsmodel, Cython, and nibabel. Installing matplotlib is recommended as we'll be plotting the results of our pRF estimation but is not required for any of the model fitting procedures in popeye.

Once you've downloaded the popeye source code and installed the aforementioned dependencies, you'll need to install popeye and build the Cython extensions I've written for speeding up the analyses.

Documentation

The code below is meant to provide only a small preview of the purpose and organization of popeye. The full documentation for popeye is available here.

Getting started

Below is a small demonstration of how to interact with the popeye API. Here, we'll generate our stimulus and simulate the BOLD response of a Gaussian pRF model estimate we'll just invent. Normally, we'd be analyzing the BOLD time-series that we collect while we present a participant with a visual stimulus.